Applications Analyst

UNC-Chapel Hill • Chapel Hill, NC

2d • Onsite

About The Position

The Division of Global Women’s Health (GWH) develops the FAMLI App, an iOS/iPadOS Software as a Medical Device (SaMD) application that pairs point-of-care ultrasound probes with embedded AI models to estimate gestational age, fetal weight, and other obstetric outputs in low-resource settings. The app is deployed with research partners on four continents and is being prepared for FDA submission. We are hiring a research software engineer to be the in-house owner of the FAMLI App as its development transitions from an external vendor to our local team. This is the central responsibility of the position: you are the engineer in charge of the app its codebase, its releases, and its day-to-day evolution. Around that core, the role includes maintaining our companion research data-collection app (Flutter/Dart with a native iOS layer), keeping our self-hosted research web tools running (including the image-annotation and QC platform our sonographers use), and providing engineering support to the machine-learning team integrating their models on-device and handling conversion and validation. Model research and ML direction are led by others; your work is engineering in support of their pipeline. This is a hands-on role covering the full stack of a deployed medical device application, working directly with clinicians, sonographers, ML scientists, and international research partners on production software deployed in active research.

Requirements

• Hands-on role covering the full stack of a deployed medical device application.
• Experience working directly with clinicians, sonographers, ML scientists, and international research partners.
• Experience with production software deployed in active research.

Responsibilities

• Be the in-house owner of the FAMLI App, including its codebase, releases, and day-to-day evolution.
• Maintain the companion research data-collection app (Flutter/Dart with a native iOS layer).
• Keep self-hosted research web tools running, including the image-annotation and QC platform.
• Provide engineering support to the machine-learning team for on-device model integration, conversion, and validation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed